Smart Devices Overload Network Signaling

April 11, 2011
Much has been said about the rising usage of data by smartphones and its impact on network capacity. Compounding this issue, however, is the fact that these signaling-hungry devices do not communicate with the wireless network in a smart or ...

Much has been said about the rising usage of data by smartphones and its impact on network capacity. Compounding this issue, however, is the fact that these signaling-hungry devices do not communicate with the wireless network in a smart or efficient manner. Instead of truly being "always on," smart devices repeatedly wake up to ping the network for updates and then go back to sleep.

With signaling accounting for as much as 60 percent of an operator's network costs, operators are looking at ways to improve interoperability between smart devices and their networks. In a 17-page white paper titled, "SOS: Signaling Overload Due to Smart Devices," Anite's Dr. Konstantino Stavropoulos describes the key methodologies used to evaluate and address this issue.

The paper begins by providing introductory information on smart devices and mobile-device radio states. According to figures from mobile network operators, a smartphone generates more signaling messages per megabyte of memory than a PC/laptop dongle. The more-or-less constant signaling between smart devices and the network burdens network resources, which could result in a network "meltdown" as the number of smart devices continues to increase. On the device end, it also can lead to sudden battery draining or slow-working applications.

To understand the impact of smart devices on mobile networks' "signaling health," reactive or proactive methodologies can be used. Examples include real-time monitoring, field testing, and laboratory testing. This white paper asserts that laboratory testing can help operators assess the signaling impact of smart devices before they are deployed. It also minimizes or eliminates the need to test the devices on the live network.

The document ends with a summary of ways in which a mobile operator may navigate the smart-device boom. Although it is a solution that is always unpopular with operators, the adding of network resources could easily counter the signaling overload. With 80 percent of mobile traffic located indoors, for example, femtocells could very well reduce the signaling load for mobile subscribers who are stationarysay, in a home or office environment.

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